Bloque B1 - Metaheurística-Vacío.ipynb

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   "source": [
    "![Aropython_logo](./static/aeropython_name_mini.png)\n",
    "###### Carlos Dorado Cárdenas\n",
    "###### Siro Moreno Martín"
   ]
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Simplifica tu vida con sistemas complejos y algoritmos genéticos"
   ]
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bloque B1: Metaheurística"
   ]
  },
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   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import random as random"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##Ejercicio 1: \n",
    "\n",
    "Sin escribir código, haya el valor de _x_ que minimiza el valor de la función _caja_negra_ en el intervalo x ∈ [-20, 20]."
   ]
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  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
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   "outputs": [],
   "source": [
    "from codigo import caja_negra"
   ]
  },
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   "source": [
    "caja_negra([20])"
   ]
  },
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   "metadata": {},
   "source": [
    "##Ejercicio 2: \n",
    "\n",
    "Usando un algoritmo de búsqueda aleatoria, minimiza la función de Bohachevski en el cuadrado x1, x2 ∈ [-100, 100]."
   ]
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=imagenes/bohachevski.png alt=\"Función de Bohachevski\" style=\"width: 500px;\"/>"
   ]
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  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
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   "outputs": [],
   "source": [
    "from codigo import bohachevski"
   ]
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  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
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   "outputs": [],
   "source": [
    "def produce_random_solution (dimensions, minimum, maximum):\n",
    "    \n",
    "    random_solution =[]\n",
    "    \n",
    "    while dimensions > 0:\n",
    "\n",
    "        random_solution.append(minimum + (maximum - minimum) * random.random())\n",
    "        \n",
    "        dimensions -= 1\n",
    "    \n",
    "    return random_solution"
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   "metadata": {
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   "source": [
    "def random_search (number_of_tries, function, dimensions, minimum, maximum):\n",
    "    \n",
    "        return best"
   ]
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##Ejercicio 3: \n",
    "\n",
    "Usando un algoritmo de ascenso de colinas, minimiza la función de Bohachevski en el cuadrado x1, x2 ∈ [-100, 100]."
   ]
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  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "def produce_tweaked_solution (solution, tweak_range, minimum, maximum):\n",
    "    \n",
    "    tweaked_solution = []\n",
    "    \n",
    "    for element in solution:\n",
    "        \n",
    "         while True:\n",
    "                \n",
    "            change = tweak_range * (random.random()-0.5)\n",
    "            \n",
    "            if minimum <= element + change <= maximum:\n",
    "                tweaked_solution.append(element + change)\n",
    "                break\n",
    "                \n",
    "    return tweaked_solution\n",
    "    "
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  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "def hill_climbing (number_of_tries, function, dimensions, minimum, maximum):\n",
    "\n",
    "    return best"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##Ejercicio 4: \n",
    "\n",
    "Usando ambos tipos de algoritmo, minimiza la función de Easom en el cuadrado x1, x2 ∈ [-100, 100]."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=imagenes/easom.png alt=\"Función de Easom\" style=\"width: 500px;\"/>"
   ]
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  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
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   "outputs": [],
   "source": [
    "from codigo import easom"
   ]
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##Ejercicio 5: \n",
    "\n",
    "Implementa un algoritmo de ascenso de colinas con reinicios aleatorios. Pruébalo con las funciones de Bohachevski e Easom. Minimiza la función de Goldstein-Price en el cuadrado x1, x2 ∈ [-2, 2]."
   ]
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=imagenes/goldstein_price.png alt=\"Función de Goldstein-Price\" style=\"width: 500px;\"/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
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   "outputs": [],
   "source": [
    "from codigo import goldstein_price"
   ]
  },
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   "cell_type": "code",
   "execution_count": 22,
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    "collapsed": false
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   "source": [
    "def hcrs (number_of_restarts, climbing_tries, function, dimensions, minimum, maximum):\n",
    "            \n",
    "    return best"
   ]
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    "HTML('<iframe src=\"http://www.psychicorigami.com/2007/04/17/tackling-the-travelling-salesman-problem-part-one/\" width=\"800\" height=\"1000\"></iframe>')"
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   "source": [
    "Si te está gustando este taller:"
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    "%%html\n",
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   "source": [
    "Carlos Dorado, Aeropython, 7 de Octubre de 2016"
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